docs: def cortex_plot_2D(the_map,
                     color=None, cmap=None, vmin=None, vmax=None, alpha=None,
                     underlay='curvature', mask=None, axes=None, triangulation=None):
      '''
      cortex_plot_2D(map) yields a plot of the given 2D cortical mesh, map.
  
      The following options are accepted:
        * color (default: None) specifies the color to plot for each vertex; this argument may take a
          number of forms:
            * None, do not plot a color over the underlay (the default)
            * a matrix of RGB or RGBA values, one per vertex
            * a property vector or a string naming a property, in which case the cmap, vmin, and vmax
              arguments are used to generate colors
            * a function that, when passed a single argument, a dict of the properties of a single
              vertex, yields an RGB or RGBA list for that vertex.
        * cmap (default: 'log_eccentricity') specifies the colormap to use in plotting if the color
          argument provided is a property.
        * vmin (default: None) specifies the minimum value for scaling the property when one is passed
          as the color option. None means to use the min value of the property.
        * vmax (default: None) specifies the maximum value for scaling the property when one is passed
          as the color option. None means to use the max value of the property.
        * underlay (default: 'curvature') specifies the default underlay color to plot for the
          cortical surface; it may be None, 'curvature', or a color.
        * alpha (default None) specifies the alpha values to use for the color plot. If None, then
          leaves the alpha values from color unchanged. If a single number, then all alpha values in
          color are multiplied by that value. If a list of values, one per vertex, then this vector
          is multiplied by the alpha values. Finally, any negative value is set instead of multiplied.
          So, for example, if there were 3 vertices with:
            * color = ((0,0,0,1), (0,0,1,0.5), (0,0,0.75,0,8))
            * alpha = (-0.5, 1, 0.5)
          then the resulting colors plotted will be ((0,0,0,0.5), (0,0,1,0.5), (0,0,0.75,0,4)).
        * mask (default: None) specifies a mask to use for the mesh; thi sis passed through map.mask()
          to figure out the masking. Those vertices not in the mask are not plotted (but they will be
          plotted in the underlay if it is not None).
        * axes (default: None) specifies a particular set of matplotlib pyplot axes that should be
          used. If axes is Ellipsis, then instead of attempting to render the plot, a tuple of
          (tri, zs, cmap) is returned; in this case, tri is a matplotlib.tri.Triangulation
          object for the given map and zs and cmap are an array and colormap (respectively) that
          will produce the correct colors. Without axes equal to Ellipsis, these would instead
          be rendered as axes.tripcolor(tri, zs, cmap, shading='gouraud'). If axes is None, then
          uses the current axes.
        * triangulation (default: None) specifies the matplotlib triangulation object to use, if one
          already exists; otherwise a new one is made.
      '''
      # parse the axes
      if axes is None: axes = matplotlib.pyplot.gca()
      # process the colors
      color = cortex_plot_colors(the_map, color=color, cmap=cmap, vmin=vmin, vmax=vmax, alpha=alpha,
                                 underlay=underlay, mask=mask)
      # finally, we can make the plot!
      return cortex_rgba_plot_2D(the_map, color, axes=axes, triangulation=triangulation)